• Journal of Institute of Control, Robotics and Systems
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• v.10 no.4
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• pp.341-349
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• 2004

In this paper, the decentralized neural network control of the reference compensation technique is proposed to control a 2-DOF inverted pendulum on an x-y plane. The cart with the 2-DOF inverted pendulum moves on the x-y plane and the 2-DOF inverted pendulum rotates freely on the x-y axis. Since the 2-DOF inverted pendulum is divided into two 1-DOF inverted pendulums, the decentralized neural network control is applied not only to balance the angle of pendulum, but also to control the position tracking of the cart. Especially, a circular trajectory tracking is tested for position tracking control of the cart while maintaining the angle of the pendulum. Experimental results show that position control of the inverted pendulum system is successful.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.28-34
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• 2012

Human generally uses three methods to keep balance. One of them is using reactive momentum such as swing an upper body or arms. In this study, we proposed a balancing controller for the reactive momentum method using an inverted pendulum. We simplified a human or a humanoid robot as a two-link inverted pendulum having two edges. In addition, we proposed a distinctive condition for controller transition. If a human is pushed, he has to change a balancing controller from using an ankle torque to using a reactive momentum or changing foot placement. When the balancing controller is changed from using an ankle torque to using a reactive momentum, it is required a proper timing to keep a stability and make smooth movement. In the experiment, the proposed controller and distinctive condition were verified.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.6
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• pp.548-553
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• 2008

In this paper, we propose a new swing-up control strategy for rotary inverted pendulums with restricted rotation range. The control law is derived from a Lyapunov function. The Lyapunov function is defined as the square of the sum of the absolute value of the total mechanical energy and weighted squares of the arm's angular displacement and velocity. By adjusting the weighting parameters in the Lyapunov function, we can affect the swing-up strategy such that the restriction on rotation range can be satisfied. Finally, we verify the performance of the proposed control law through simulation and experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.8
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• pp.623-631
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• 2003

We have fabricated the two-dimensional inverted pendulum system and designed its controller. The two-dimensional inverted pendulum system, which is composed of X-Y table, is actuated through timing belt by each of two geared DC motors. And the control goal is that the rod is always kept to a vertical position to any distrubance and is quickly moved to the desired position. Because this system has generally nonlinear dynamic characteristics and X-axis and Y-axis move together, it is very difficult to find its exact mathematical model and to design its controller. Therefore, we have designed the PID controller with simple structure and excellent performance. Genetic algorithm(GA), which is blown as one of probabilistic searching methods, and human's heuristic control strategy are introduced to design an optimal PID controller. The usefulness of the proposed GA based PID coefficient searching technique is verified through the experiments and computer simulations.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.3
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• pp.157-163
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• 2000

In this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algoithm(RVEGA) was presented for stabilization of an Inverter Pendulum(IP) system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the determinations of input or output neuron, the deleted neuron and the activation functions types are given according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. Through the simulations, we showed that the finally acquired optimal ENNC was successfully applied to the stabilization control of an IP system.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.705-707
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• 2018

Rotary Inverted Pendulum 은 제어분야에서 비선형 제어 시스템을 설명하기 위해 자주 사용되어왔다. 본 논문은 강화학습 에이전트의 환경으로써 Rotary Inverted Pendulum 을 도입하였다. 이를 통해서 강화학습이 실제 세계에서의 복합적인 문제를 해결할 수 있음을 보인다. 강화학습 에이전트의 가상 환경과 실제 환경을 맵핑시키기 위해서 Ethernet 연결 위에 MQTT 프로토콜을 사용하였으며 이를 통해서 경량화된 IoT 분야에서의 강화학습의 활용도를 조명한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.493-495
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• 2019

제어 분야의 가장 기초적인 시스템인 Rotary Inverted Pendulum 을 제어하기 위하여, 본 논문에서는 강화학습에서 Deep Q-Network 과 함께 대표적인 알고리즘으로 알려진 Asynchronous Advantage Actor-Critic 을 활용하여 다중 디바이스 제어를 설계한다. Deep Q-Network 알고리즘을 활용한 기존 연구와 동일한 방식으로 실 세계의 물리 에이전트와 가상 환경을 맵핑시키며, 스위치를 통하여 로컬 에이전트와 글로벌 네트워크 간 통신을 구성한다. 본 논문에서는 분산 Asynchronous Advantage Actor-Critic 을 이용함으로써 실 세계의 다중 에이전트 제어를 위한 강화 학습의 활용 가능성을 조명한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.185-188
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• 2009

In this paper, Position Controller for balance of Seesaw System design using PID Algorithm. Seesaw System is that it's system use widely to analyze of ship or flight dynamics, Inverted Pendulumand, Robot System, manage system for theory of modern control system and all sorts of analysis. In case of Seesaw System, it's necessity that understand and analysis of system and correct selection of parameter because the system is strong nonlinear control system. It guarantees efficiency and stability to adapt quickly for disturbance or change of controller from PID Algorithm of guarantee safe from simple and long history and PSO(Particle Swarm Optimization) that sort of metaheuristic optimization that need to accuracy and fast PID parameter tuning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.4
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• pp.875-885
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• 1999

This paper presents an application of LMI-based techniques to the mixed $H_2/ H_\infty$ control of an inverted pendulum. The linear model of the inverted pendulum represented by an LFR(Linear Fractional Representation) model of uncertainties is derived. Considered uncertainties are three nonlinear components and a parameter uncertainty Augmenting the LFR model by adding weighting functions, we get a generalized plant, for which we design a mixed $H_2/ H_\infty$ controller using the LMI technique. To evaluate control performances and robust stability of the mixed $H_2/ H_\infty$ controller designed, we compare it with the $ H_\infty$controller through the simulation and experiment. The mixed $H_2/ H_\infty$ controller shows the better control performances and robust stability than the $H_\infty$controller in the sense of pendulum angle.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.797-799
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• 1999

In this paper, the edge intensification and detection algorithm which is one of image processing operations is considered. Edge detection algorithm is the most useful and important method for image processing or image analysis. The vision system based on these processing and concerned in specific project is proposed and is applied to the inverted pendulum in order to automatically acquire the angles between the bar and the perpendicular reference line. In this paper, the angles that are obtained from some images of computer vision system can offer useful informations for control of real inverted pendulum system. Next, the inverted pendulum will be controlled by the proposed method.